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The relationship between alcohol consumption and body weight is the subject of inconclusive studies. Findings of these studies range from increase in body weight to a small decrease among women who begin consuming alcohol. [1] [2] Some of these studies are conducted with numerous subjects; one involved nearly 8,000 and another 140,000 subjects.
In statistics, shrinkage is the reduction in the effects of sampling variation. In regression analysis, a fitted relationship appears to perform less well on a new data set than on the data set used for fitting. [1] In particular the value of the coefficient of determination 'shrinks'.
Studies on alcohol and weight loss are mixed, however. One 2020 analysis of more than 280,000 people found that those who drank wine had lower BMIs than those who didn’t drink wine.
Under conditions of moderate alcohol consumption where blood alcohol levels average 0.06–0.08 percent and decrease 0.01–0.02 percent per hour, an alcohol clearance rate of 4–5 hours would coincide with disruptions in sleep maintenance in the second half of an 8-hour sleep episode.
Alcohol tolerance is increased by regular drinking. [1] This reduced sensitivity to the physical effects of alcohol consumption requires that higher quantities of alcohol be consumed in order to achieve the same effects as before tolerance was established. Alcohol tolerance may lead to (or be a sign of) alcohol dependence. [1]
Richard Piper, an alcohol harm-reduction expert, used to drink heavily. His "dry by default" rule helped him reduce the risks of drinking without going sober. This story was originally published ...
Kelly Ripa revealed on "Live with Kelly and Mark" that she gained an unexpected 12 pounds when she stopped drinking. Dr. Kathleen Jordan discusses alcohol's impact on weight.
For normally distributed random variables inverse-variance weighted averages can also be derived as the maximum likelihood estimate for the true value. Furthermore, from a Bayesian perspective the posterior distribution for the true value given normally distributed observations and a flat prior is a normal distribution with the inverse-variance weighted average as a mean and variance ().